• Spatial Information Research
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• v.20 no.5
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• pp.25-35
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• 2012

This study compared the influence of water quality according to the data sources of spatial information. Firstly, land cover map was constructed through image classification of Daecheong-dam basin and the accuracy of image classification from satellite image showed high as 88.76% in comparison with the large-scaled land cover map in Ministry of Environment, to calculate Event Mean Concentration (EMC) by land cover that impact on the evaluation of nonpoint source pollutant loads. Also curve number and direct runoff were calculated by spatial overlay with soil map and land cover map from image classification. And Seokcheon and Daecheong-Dam basin showed high in the analysis of curve number and direct runoff. Samgacheon-Joint and Sokcheon-Downstream basin showed high in the nonpoint source pollutant loads of BOD from direct runoff and EMC. And Samgacheon-Joint and Bonghwangcheon- Downstream basin showed high in the nonpoint source pollutant loads of TN and TP. Nonpoint source pollutant loads from image classification were compared with those by the land cover map from Ministry of Environment to present the effectivity of nonpoint source pollutant loads from satellite image. And Daecheong-Dam Upstream basin showed high as 10.64%, 11.70% and 20.00% respectively in the errors of nonpoint source pollutant loads of BOD, TN, and TP. Therefore, it is desirable that spatial information including with paddy and dry field is applied to the evaluation of nonpoint source pollutant loads in order to simulate water quality of basin effectively.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.6
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• pp.1027-1037
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• 2023

This paper presents an efficient method for generating informative apparel fit comments by analyzing 122 fit reviews found in 7 menswear patternmaking textbooks, which include both domestic and foreign sources. The fit reviews for menswear were categorized into top and bottoms, and the expressions varied based on body parts, causes, and fit issue appearances. The causes of fit issues could be attributed to size errors and structural errors in both top and bottoms. Both top and bottoms had fit reviews concerning unique body types, but it could cause trouble among learners as both were based on unclear criteria for body type classification and lacked relevant explanations. Common fit issue appearances included compound wrinkles, pulling wrinkles, sagging wrinkles, and garment being away from the body. No clear correlation was observed between the causes of fit issues and specific appearances. Limitations were identified in using textbooks as educational data, such as inconsistent solutions for different body types or fit issues, and the presence of ambiguous visual materials. As a result, strategies such as categorizing fit issue appearances, providing 3D visual examples with subcategorized causes, body types and parts could enhance quality of fit reviews and improve fit outcomes in clothing production systems.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.37-55
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• 2022

This study presents the plans to derive quality items for develop the data quality standard for ensuring the quality of 3D building geospatial data in NDT(National Digital Twin). This paper is organized as follows. The first section briefly examines various factors that impact the quality of 3D geospatial data, and proposes the role and necessity of the data quality standard as a means of addressing the data errors properly and also meeting the minimum requirements of stakeholders. The second section analyzes the relationship between the standards - building data model for NDT and ISO 19157: Geospatial data quality - in order to consider directly relevant standards. Finally, we suggest three plans on developing NDT data quality standard: (1) the scope for evaluating data quality, (2) additional quality elements(geometric integrity, geometric fidelity, positional accuracy and semantic classification accuracy), and (3) NDT data quality items model based on ISO 19157. The plans reveled through the study would contribute to establish a way for the national standard on NDT data quality as well as the other standards associated with NDT over the coming years.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.303-309
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• 2008

Landcover map can use to establish basic national environment policy as main data predicting living place, counting pollution like a atmosphere, water and forest part. During the 1998-2005 years, Korean government made landcover maps using satellite image for part of south Korea. Landcover maps are offered free for public purpose to university and institute. So, it used basic data for policy and research parts. There are some problems for application parts because of inconsistency. So, in this study, to estimate accuracy of source data by quality checking for landcover maps. As a result, there are some errors like classification inconsistencies. So, it need verification process for landcover maps.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.4
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• pp.361-369
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• 2018

The ship surveyor makes a scheme of reasonable ship operation by examining whether the ship has been properly constructed in accordance with the rule of classification societies and international conventions or whether the facilities of the ship in operation meet the standard stipulated by law. Even though the ship surveyors of classification society generally consist of people who have the skill of design or operation of a ship, it takes a long time to train a surveyor to the maturity level. This paper describes the development of survey simulator based on virtual ship environment that enables the surveyor minimize trial and errors to survey the ships. By using VR(Virtual Reality) based survey simulator, surveyors possibly achieve improvement of competence in survey quality by means of safe and immersive training environment. In order to improve the usability and utility of the VR simulator, the ship 3D model has been generated using 3D CAD model for design and production in shipyard. Through this, we suggested the possibility of consistent use of 3D model as the digital twin of a ship.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.348-358
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• 2022

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.101-108
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• 2023

Although the proportion of coal-fired power generation is decreasing, efficient operating technology is needed to continuously invest in facilities and reduce maintenance costs until it is abolished. Boilers, one of the main facilities of power plants, operate for a long time in harsh environments of high temperature and high pressure. In addition, damage due to deterioration is likely to occur depending on the fuel and tube material used. It is very important to judge soundness because damage caused by deterioration adversely affects facility operation. Previously, replication method was used to analyze the progress of deterioration. In the replication method, pre-treatment such as chemical treatment is performed on the boiler tube in the field, the area is reproduced by attaching a film, and the replicated film is determined by an expert in the laboratory with an expensive microscope. However, this method involves substantial costs and time requirements, as well as the possibility of human errors. To address these issues, we developed a mobile health assessment system in this research. Since it is detachable and takes images in real time, this system enables swift evaluations across a broad range and facilitates the assessment of preprocessing quality. In addition, it was intended to reduce existing human mistakes by developing a degradation classification algorithm using the merger cluster method.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.417-428
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• 2023

The demolition of domestic infrastructures mirrors other significant construction initiatives in presenting a markedly high accident rate. A comprehensive investigation into the origins of such accidents is crucial for the prevention of future incidents. Upon detailed inspection, the causes of demolition construction accidents are multifarious, encompassing unsafe worker behavior, hazardous conditions, psychological and physical states, and site management deficiencies. While statistics relating to demolition construction accidents are consistently collated and reported, there exists an exigent need for a more foundational cause categorization system based on accident type. Drawing from Heinrich's Domino Theory, this study classifies the origins of accidents(unsafe behavior, unsafe conditions) and human errors(human factors) as per the type of accidents experienced during demolition construction. In this study, a three-step model of QFD-FMEA(Quality Function Deployment - Failure Mode Effect Analysis) is employed to systematically categorize accident causes according to the types of accidents that occur during demolition construction. The QFD-FMEA method offers a technique for cause classification at each stage of the demolition process, including direct causes(unsafe behavior, unsafe environment), and human errors(human factors) through a tri-stage process. The results of this accident cause classification can serve as safety knowledge and reference checklists for accident prevention efforts.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.35-42
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• 2008

In the national economy, rate of service industry is going up to compare with manufacture industry. In spite of getting lots of results to be introduced 6 sigma methodology in Korea, many service companies is suffering with trial and errors. Also 6 sigma isn't settled perfect yet. The reason for that, 6 sigma have been applied to various service without considering. Therefore, this research shows to you right practice plans for service industrial classification to check structural features and difference. So this research seeks methods for revitalization of 6 sigma methodology in service industry after checking existed research, case study for companies to be applied by 6 sigma. As the result, service industry is forecasted to contribute greatly in economic growth and employment enlargement through enlargement of service role in manufacturing industry production as well as by itself.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1255-1255
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• 2001

The study used 356 veal calf meat samples received from Finland (n=16), France (n=109), Italy (n=81) and The Netherlands (n=150). Calves were raised under experimental protocols that compared feeding and housing practices normally used in each county to treatments aiming at improving animal welfare. Samples were taken at the $8^{th}$ rib of Longissimus thoracis muscle 24h after slaughter, They were kept refrigerated ( $2-4^{\circ}C$) under vacuum package for 6d and then frozen ($-20^{\circ}C$) until meat quality evaluation. Measurements included pH, color (Hunter Lab system), shear force, chemical composition (DM, Ash, Ether Extract, collagen and haematin content), weight and area cooking losses and a sensory evaluation by a group of panelists. A sample of meat was ground with a blade mill and scanned in duplicate between 1100 and 1498 nm (FOSS NIR Systems 5000). WinISI software was used to develop a discriminating equation using NIR spectra (SNV-detrend, derivative=1, gap=4nm, smooth=4nm). The Proc ANOVA and DISCRIM of SAS were used for all the laboratory determinations. County of production had a significant (P<0.01) effect on all the parameters. However, discriminant analysis using any or few laboratory parameters resulted in great errors of county classification. A more accurate (98.8%) classification was obtained only when using all the laboratory parameters. NIRS classified correctly 354 of the 356 samples (99.4%). Provided with a larger data set, NIRS could be used to identify country of production of veal meat.